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Performing Content-Based Image Retrieval (CBIR) from Internet databases connected through Peer-to-Peer (P2P) network, abbreviated as P2P-CBIR, helps to effectively explore the large-scale image database distributed over connected peers. Decentralized unstructured P2P framework is adopted in our system to compromise with the structured one while still reserving flexible routing control when peers join/leave...
Processing images for specific targets on a large scale has to handle various kinds of contents with regular processing steps. To segment objects in one image, we utilized dual multiScalE Graylevel mOrphological open and close recoNstructions (SEGON) to build a background (BG) gray-level variation mesh, which can help to identify BG and object regions. It was developed from a macroscopic perspective...
Performing image preprocessing for specific targets, e.g., foreground (FG) segmentation and feature extraction, on the scale of databases is challenging. For volume image FG segmentation, we proposed to utilize dual multi-scale graylevel morphological open/close by reconstruction to simulate background (BG) gray-level variational mesh to identify FG regions. It is developed from a global perspective...
A simple and regular foreground identification (FGID) method is proposed for image indexing. The gray-level morphological open/close by reconstruction (MOR/MCR) is operated on one image in a dual and multi-scale approach to construct a background gray-level mesh to distinguish foregrounds (FGs). The highly regular MOR/MCR operations make it feasible to deal with FG segmentation of volume images. The...
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